An Iris Recognition System by Laws Texture Energy Measure Based k-NN Classifier

dc.contributor.authorAcar, Emrullah
dc.contributor.authorOzerdem, Mehmet Sirac
dc.date.accessioned2024-04-24T17:47:30Z
dc.date.available2024-04-24T17:47:30Z
dc.date.issued2013
dc.departmentDicle Üniversitesien_US
dc.description21st Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2013 -- CYPRUSen_US
dc.description.abstractBiometric recognition technology is correlated generally with very expensive top secure applications. Iris recognition system is one of the effective biometric recognition systems. The main purpose of this study is to recognize the human from different eye images according to their iris texture characteristics. The digital crop images are derived from CASIA iris image database. The texture feature vectors are extracted from the local iris regions by using Laws Texture Energy Measure (TEM) which is a new method for image texture feature extraction. The obtained feature vectors are separated by k-Nearest Neighbor (k-NN) classifier as taking the neighbor number (k) parameter in different values and the performance results of each system are compared according to disparate k values. Finally, the best average performance is observed as 80.74 % in k=1 and 2 neighbors structure of k-NN classifier.en_US
dc.identifier.isbn978-1-4673-5563-6
dc.identifier.isbn978-1-4673-5562-9
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/11468/22551
dc.identifier.wosWOS:000325005300237
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2013 21st Signal Processing and Communications Applications Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectIris Recognitionen_US
dc.subjectImage Processingen_US
dc.subjectClassificationen_US
dc.subjectK-Nn Classifieren_US
dc.subjectLaws Temen_US
dc.titleAn Iris Recognition System by Laws Texture Energy Measure Based k-NN Classifieren_US
dc.titleAn Iris Recognition System by Laws Texture Energy Measure Based k-NN Classifier
dc.typeConference Objecten_US

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